Modeling and learning social influence from opinion dynamics under attack is coming at 01/13/2020 - 11:00am
Rogers 230 Mon, 01/13/2020 - 11:00am Anna Scaglione Professor, Electrical and Computer Engineering, Arizona State University Abstract: Opinion dynamics models aim at capturing the phenomenon of social learning through public discourse. While a functioning society should converge towards common answers, the reality often is characterized by divisions and polarization. This talk reviews the key models that capture social learning and its vulnerabilities. In particular, we review models that explain the effect of bounded confidence and social pressure from zealots (i.e. fake new sources) and show how very simple models can explain the trends observed when social learning is subject to these phenomena. We their influence exposes trust different agents place on each other and introduce new learning algorithms that can estimate how agents influence each other. NOTE: This seminar is presented by the IEEE Signal Processing Society, Oregon Chapter & School of EECS and is not part of the EECS colloquium series. Bio: Read more: https://eecs.oregonstate.edu/colloquium/modeling-and-learning-social-inf... [1] [1] https://eecs.oregonstate.edu/colloquium/modeling-and-learning-social-influence-opinion-dynamics-under-attackopinion-dynamics
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